Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Opinion mining from noisy text data
Proceedings of the second workshop on Analytics for noisy unstructured text data
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
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Increasing Internet users has created enormous important information of users in Internet. Opinion mining is technology that extracts meaningful opinions from that huge information. Becoming a hot research area, opinion mining has been studied in many different ways. These studies are mostly based on reviews, blogs. However, this paper focuses on messenger which generates many messages containing opinions of users. As messages may contain many opinions unrelated to our purpose, our aim is to extract only related opinions and features. Our approach initially collects messages from messengers and employs localized linguistic technique to extract candidate messages, opinions and features. Thereafter, we extract features from candidate features using association rule mining. Finally we summarize extracted opinions and features.